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This function allows to summarize included treatments and treatment comparisons in a data set.


               which = c("treatments", "comparisons"),
               # Metapsy standard variables
               .study.var = "study",
               .condition = "condition",
               .condition.specification = "multi",
               .groups.column.indicator = c("_arm1", "_arm2"),
               .trt.indicator = "arm",
               .n.vars = c("n", "n_change", "totaln", "N"),
               # Output
               html = TRUE)



data.frame. Effect size data in the wide format, as created by calculateEffectSizes. For the other default settings to be applicable, the data set should follow the Metapsy data standard. Alternatively, one can also provide an metapsyDatabase object as returned by metapsyData::getData(), or a meta-analysis object returned by runMetaAnalysis().


Should the data set be summarized with respect to the included treatments ("treatments") or treatment comparisons ("comparisons")? Defaults to "treatments".


character. The name of the variable in the data set in which the study labels are stored.


character. The prefix of the two variables in data in which the conditions (e.g. "guided iCBT", "waitlist") of the trial arm comparison are stored.


character. The prefix of the two variables in the dataset which provide a "specification" of the trial arm condition in multiarm trials.


character. A character vector with two elements, representing the suffix used to differentiate between the first and second arm in a comparison.


character. A character specifying the name used to indicate the treatment arm.


character. A character vector which includes the names of all variables in the data set in which sample size information is stored. Only the prefix is needed, where .groups.column.indicator provides the suffixes.


logical. Should an HTML table be created for the results? Default is TRUE.


Returns an object of class "exploreStudies". This object includes a list object called summaryin which the counts for distinct treatments (conditions) and comparisons (comparisons) are summarized, as well as a data.frame data. This data frame includes the initially provided data set collapsed by study (so that each row represents one study). To this data set, variables are added that encode how many arms with a specific condition are included in the trial (e.g. if cbt=2, this means that two CBT groups are included in the trial), as well as the number of distinct comparisons, and the sample size of both (these columns all start with n.). This can be helpful to perform further descriptive analyses.


Using the variables provided in the .n.vars argument, exploreStudies calculates the arm- and study-specific sample sizes. If no adequate information is provided, sample sizes cannot be calculated for a study. If this is the case, a warning is printed, pointing to the studies with missing sample size information.


Mathias Harrer mathias.h.harrer@gmail.com, Paula Kuper paula.r.kuper@gmail.com, Pim Cuijpers p.cuijpers@vu.nl


if (FALSE) {
# Explore studies in built-in dataset
exploreStudies(depressionPsyCtr, "treatments") 
exploreStudies(depressionPsyCtr, "comparisons") 

# - Extract metapsy database using metapsyData
# - Filter CBT and PST studies
# - Run a meta-analysis and explore synthesize studies
getData("depression-psyctr", version="22.0.2") %>% 
  filterPoolingData(condition_arm1 %in% c("cbt", "pst")) %>% 
  runMetaAnalysis(which.run = c("combined")) -> res

exploreStudies(res, "comparisons")